In the last 10 years a number of new global datasets have been created and new, more
sophisticated algorithms have been designed to classify land cover. GlobCover and MODIS v.5
are the most recent global land cover products available, where GlobCover (300 m) has the
finest spatial resolution of other comparable products such as MODIS v.5 (500 m) and
GLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain has
decreased when comparing these two latest products. This disagreement is also evident spatially
when examining maps of cropland and forest disagreement between GLC-2000, MODIS and
GlobCover. The analysis highlights the continued uncertainty surrounding these products, with
a combined forest and cropland disagreement of 893 Mha (GlobCover versus MODIS v.5). This
letter suggests that data sharing efforts and the provision of more in situ data for training,
calibration and validation are very important conditions for improving future global land cover products.